Correlation bounds against monotone NC

Abstract

This paper gives the first correlation bounds under product distributions, including the uniform distribution, against the class mNC1 of polynomial-size O(log n)-depth monotone circuits. Our main theorem, proved using the pathset complexity framework introduced in [56], shows that the average-case k-CYCLE problem (on Erdos-Renyi random graphs with an appropriate edge density) is [EQUATION] hard for mNC1. Combining this result with O'Donnell's hardness amplification theorem [43], we obtain an explicit monotone function of n variables (in the class mSAC1) which is [EQUATION] hard for mNC1 under the uniform distribution for any desired constant e > 0. This bound is nearly best possible, since every monotone function has agreement [EQUATION] with some function in mNC1 [44].Our correlation bounds against mNC1 extend smoothly to non-monotone NC1 circuits with a bounded number of negation gates. Using Holley's monotone coupling theorem [30], we prove the following lemma: with respect to any product distribution, if a balanced monotone function f is [EQUATION] hard for monotone circuits of a given size and depth, then f is [EQUATION] hard for (non-monotone) circuits of the same size and depth with at most t negation gates. We thus achieve a lower bound against NC1 circuits with [EQUATION] log n negation gates, improving the previous record of 1/6 log log n [7]. Our bound on negations is half optimal, since ⌈log(n + 1)⌉ negation gates are known to be fully powerful for NC1 [3, 21].